### Terms and Conditions
- [x] I agree to the [Grant Agreement](https://9ba4718…c-5c73-47c3-a024-4fc4e5278803.usrfiles.com/ugd/9ba471_f81ef4e4b5f040038350270590eb2e42.pdf) terms if funded
- [x] I agree to [Provide KYC information](https://9ba4718c-5c73-47c3-a024-4fc4e5278803.usrfiles.com/ugd/9ba471_7d9e73d16b584a61bae92282b208efc4.pdf) if funded above $50,000 USD
- [x] I agree to disclose conflicts of interest
- [x] I agree to adhere to the [Code of Conduct](https://forum.zcashcommunity.com/t/zcg-code-of-conduct/41787) and [Communication Guidelines](https://forum.zcashcommunity.com/t/zcg-communication-guidelines/44284)
- [x] I understand all milestone deliverables will be validated and accepted by their intended users or their representatives, who will confirm that the deliverables meet the required quality, functionality, and usability for each user story.
- [x] I agree that for any new open-source software, I will create a `CONTRIBUTING.md` file that reflects the high standards of Zcash development, using the [`librustzcash` style guides](https://github.com/zcash/librustzcash/blob/main/CONTRIBUTING.md#styleguides) as a primary reference.
- [x] I understand when contributing to existing Zcash code, I am required to adhere to the project specific contribution guidelines, paying close attention to any [merge](https://github.com/zcash/librustzcash/blob/main/CONTRIBUTING.md#merge-workflow), [branch](https://github.com/zcash/librustzcash/blob/main/CONTRIBUTING.md#branch-history), [pull request](https://github.com/zcash/librustzcash/blob/main/CONTRIBUTING.md#pull-request-review), and [commit](https://github.com/zcash/librustzcash/blob/main/CONTRIBUTING.md#commit-messages) guidelines as exemplified in the `librustzcash` repository.
- [x] I agree to post request details on the [Community Forum](https://forum.zcashcommunity.com/c/grants/33)
- [x] I understand it is my responsibility to post a link to this issue on the [Zcash Community Forums](https://forum.zcashcommunity.com/c/grants/33) after this application has been submitted so the community can give input. I understand this is required in order for ZCG to discuss and vote on this grant application.
### Application Owners (@Octocat, @Octocat1)
@MonzaTech
### Organization Name
Monza Tech LLC
### How did you learn about Zcash Community Grants
Google
### Requested Grant Amount (USD)
45000
### Category
Infrastructure
### Project Lead
```project-lead.yaml
Name:
Alexandre Figueras
Role:
Founder & Project Lead
Background:
Alexandre is a technology entrepreneur specializing in AI, data infrastructure, and decentralized systems. He has led multiple innovation projects under Monza Tech, focusing on applied AI for critical infrastructure, grid resilience, and secure communications.
Responsibilities:
Overseeing strategic direction, technical architecture, partner coordination, and delivery of all milestones. Ensures seamless integration of Sentinel Grid with blockchain infrastructure and Zcash ecosystem priorities.
```
### Additional Team Members
```team-members.yaml
• Name: Sofia Ivanova
Role: Data Science Lead
Background: AI researcher and psychologist with experience in predictive modeling, behavioral analytics, and resilience systems. Previously led applied ML projects focused on risk assessment and anomaly detection.
Responsibilities: Designing and training Sentinel Grid’s AI models for predictive analytics and integrating risk insights into the Zcash infrastructure layer.
• Name: Matias Pini
Role: Systems Engineer & Technical Operations
Background: Experienced engineer with a background in cloud infrastructure, automation, and distributed computing. Previously contributed to high-availability systems for energy and logistics networks.
Responsibilities: Responsible for infrastructure deployment, validator setup, node monitoring, and ensuring uptime for AI and blockchain integrations.
• Name: Howard McIntosh
Role: Strategic Partnerships & Compliance
Background: Business executive with experience in enterprise operations and compliance strategy across regulated industries.
Responsibilities: Managing strategic partnerships, compliance documentation, and grant reporting alignment with Zcash ecosystem goals.
```
### Project Summary
Sentinel Grid is an AI-powered infrastructure resilience platform that integrates with blockchain networks like Zcash to predict, prevent, and mitigate critical system failures across energy, transport, and communication networks.
### Project Description
Sentinel Grid is an AI-driven resilience and monitoring platform designed to secure critical infrastructure by combining predictive analytics, blockchain verification, and decentralized data integrity. The system continuously analyzes energy, transport, and communication networks to detect early signs of disruption, equipment failure, or cyber threats before they escalate.
By integrating with the Zcash ecosystem, Sentinel Grid ensures that incident data and infrastructure telemetry are stored immutably, providing transparent audit trails and privacy-preserving verification. The project’s goals include enhancing real-time situational awareness, reducing downtime, and demonstrating how AI and privacy-focused blockchain technology can work together to create safer, more resilient smart cities and national systems.
### Proposed Problem
Modern infrastructure networks—such as energy grids, transport systems, and communication hubs—remain highly vulnerable to failures, cyberattacks, and data manipulation due to centralized monitoring systems and delayed response mechanisms. These vulnerabilities can lead to widespread outages, economic losses, and public safety risks. Sentinel Grid addresses this challenge by using AI and blockchain to detect anomalies early, predict potential failures, and ensure that all incident and performance data remain secure, tamper-proof, and verifiable through Zcash’s privacy-preserving architecture.
### Proposed Solution
Sentinel Grid combines artificial intelligence with blockchain verification to create a decentralized resilience layer for critical infrastructure. Our AI models analyze sensor data in real time to detect anomalies, predict system failures, and recommend preventive actions before disruptions occur. Each event and data stream is securely logged on the Zcash blockchain, ensuring immutable and privacy-preserving auditability. This approach eliminates reliance on centralized systems, enhances transparency, and allows infrastructure operators to act quickly and confidently while maintaining data integrity and confidentiality across all monitored assets.
### Solution Format
The solution will be delivered as a software platform consisting of three key components:
1. Sentinel AI Engine – a machine learning module for real-time anomaly detection and predictive maintenance across infrastructure systems.
2. Blockchain Integration Layer – a Zcash-based module for secure, verifiable, and privacy-preserving event logging.
3. Dashboard Interface – a web-based visualization tool providing live monitoring, risk alerts, and system analytics.
All components will be accompanied by technical documentation, open-source modules, and an implementation report demonstrating Zcash integration.
### Dependencies
The project depends on several key technical and collaborative components:
• Zcash blockchain infrastructure for secure, privacy-preserving data logging.
• Machine learning frameworks such as TensorFlow and PyTorch for developing predictive models.
• Data integration APIs from infrastructure operators (energy, transport, communication) to train and validate the AI models.
• Cloud or hybrid computing resources for AI model training and simulation environments.
• Collaborations with cybersecurity specialists and infrastructure partners for real-world testing and calibration.
• Frontend technologies (React, Node.js) for the monitoring dashboard and user interface.
### Technical Approach
We will build Sentinel Grid as a modular, privacy-preserving monitoring stack:
• Data pipeline: Ingest real-time telemetry (SCADA, IoT, logs, network flows) via secure gateways; normalize into time-series and event streams.
• Detection engine: Use a mix of time-series ML (LSTM/Temporal CNN/Transformers), gradient boosting, and graph neural networks to model asset behavior and interdependencies and flag anomalies, precursors to faults, and cascading risks.
• Scoring & response: Assign risk scores per asset/event; trigger automated playbooks (alerts, throttling, isolation recommendations) via rules + learned policies.
• Zcash integration: Hash and commit critical alerts, model versions, and mitigation actions to Zcash using shielded transactions for integrity + confidentiality; zk-friendly logging to prove events/actions occurred without exposing sensitive ops data.
• Stack & tools: Python, PyTorch/TensorFlow, FastAPI, PostgreSQL/TimescaleDB, Docker/Kubernetes, React for dashboard, plus hardened APIs for operators to integrate into existing NOC/SOC tooling.
### Upstream Merge Opportunities
Our project plans limited but meaningful interaction with upstream Zcash software:
• Repositories: We plan to fork and extend the zcashd and librustzcash repositories to enable lightweight integration of secure audit logs via shielded transactions and hashed metadata embedding.
• Planned modifications:
• Add a structured metadata field for operational event commitments.
• Implement APIs to automate shielded transaction creation for system-to-chain logging.
• Extend wallet functionality to support automated batching of integrity proofs.
• Upstream benefit: These enhancements could allow other developers to build privacy-preserving data integrity or IoT logging applications on Zcash, expanding its use cases beyond payments.
• Coordination: We will coordinate with Zcash developers for design validation and maintain compatibility with protocol updates.
• Timeline: Initial fork and testing in months 1–2, followed by community feedback and potential merge proposal by month 4.
### Hardware/Software Costs (USD)
7800
### Hardware/Software Justification
These hardware and software costs are essential to develop, test, and validate Sentinel Grid’s real-time AI and blockchain integration.
• Cloud infrastructure is required for large-scale simulation, model training, and deployment testing across distributed datasets.
• Edge hardware (IoT nodes and gateways) allows us to emulate real-world telemetry from energy and communication networks, ensuring that our Zcash-based integrity layer performs under operational conditions.
• GPU and workstation resources are needed for training anomaly detection and risk prediction models efficiently.
• Software licenses and APIs support visualization, monitoring, and secure communication layers.
• Security tools ensure encryption, key management, and safe signing of shielded transactions during testing and deployment.
Together, these components make the prototype technically feasible, secure, and scalable.
### Service Costs (USD)
6500
### Service Costs Justification
These service costs are essential to ensure Sentinel Grid’s reliability, security, and technical integrity.
• Blockchain node hosting is required to run Zcash testnet and mainnet environments for validating shielded transactions and interoperability.
• Data sourcing services provide realistic, anonymized infrastructure datasets necessary to train and evaluate the AI risk models accurately.
• External audits are critical for verifying smart contract security, data encryption, and compliance with privacy standards.
• Monitoring and uptime services allow continuous performance tracking and stress testing of the network under simulated load conditions.
Together, these services guarantee that the system is secure, compliant, and production-ready.
### Compensation Costs (USD)
24000
### Compensation Costs Justification
Team compensation reflects each member’s technical expertise and the project’s short development timeline. Rates are benchmarked against industry standards for blockchain and AI development.
• AI/Blockchain Engineer ($10,000): Senior-level professional with experience in smart contract security and decentralized infrastructure, responsible for the core Sentinel Grid protocol and Zcash integration.
• Data Scientist ($6,000): Mid-level expert in predictive analytics and ML model training, developing algorithms to detect infrastructure anomalies.
• Full Stack Developer ($4,000): Responsible for user interface, backend connectivity, and API reliability.
• Project Manager / Research Lead ($3,000): Oversees coordination, documentation, and communication with grant stakeholders.
• Security Engineer ($1,000): Performs audits, tests, and encryption verification.
Each role is essential for delivering a production-ready, secure, and validated implementation within the proposed grant period.
### Total Budget (USD)
45000
### Previous Funding
No
### Previous Funding Details
_No response_
### Other Funding Sources
No
### Other Funding Sources Details
_No response_
### Implementation Risks
Implementation Risks:
1. Technical Integration Challenges: Integrating Sentinel Grid’s AI analytics with Zcash’s privacy layer may require custom cryptographic bridges or performance optimization.
2. Data Availability: Access to high-quality infrastructure and operational datasets is crucial for accurate model training; limited or delayed access could slow progress.
3. Regulatory Constraints: Compliance with privacy and energy data regulations may introduce delays depending on regional policies.
4. Resource Constraints: As a lean, high-skill team, unexpected technical issues or personnel changes could impact development timelines.
5. Ecosystem Dependencies: Integration success partly depends on timely collaboration with Zcash maintainers and external partners.
All risks are mitigated through modular development, milestone-based reviews, and redundant data simulation environments.
### Potential Side Effects
Potential Side Effects:
1. Computational Load: Running AI-driven monitoring models may increase energy consumption or infrastructure load if not properly optimized.
2. Data Privacy Concerns: Despite encryption and anonymization, integrating operational data with blockchain systems could raise privacy questions if mismanaged.
3. Over-Reliance on Automation: Users or operators might depend too heavily on predictive alerts, reducing human oversight in critical situations.
4. Market Distortion: If widely adopted, predictive insights could influence energy or transport market behaviors, creating short-term volatility.
Mitigation strategies include continuous system audits, transparent reporting, privacy-first data handling, and maintaining human validation in operational workflows.
### Success Metrics
Success Metrics:
1. Technical Performance: Successful integration of Sentinel Grid’s AI analytics with Zcash privacy infrastructure, validated through benchmark testing and public testnet deployment.
2. Accuracy & Reliability: Achieving >90% prediction accuracy for infrastructure anomalies in simulated and real-world environments.
3. Operational Uptime: Maintaining system uptime above 99.5% during test runs and mainnet operations.
4. Ecosystem Adoption: At least 3 pilot collaborations with energy or data infrastructure partners leveraging the Zcash-integrated module.
5. Community Engagement: Open-source contributions, documentation quality, and developer adoption within the first 6 months of release.
### Startup Funding (USD)
5000
### Startup Funding Justification
The requested $45,000 will fund the development and deployment of Sentinel Grid’s Zcash-integrated prototype. The allocation includes:
• $15,000 for infrastructure setup — secure compute, storage, and network nodes.
• $20,000 for developer compensation — AI, blockchain, and backend integration.
• $5,000 for testing, simulation, and documentation.
• $5,000 for validation, ecosystem coordination, and operational contingencies.
This initial funding will cover the first 3 months of work to deliver a functional, privacy-preserving AI resilience layer aligned with Zcash’s technical and ethical standards.
### Milestone Details
```milestones.yaml
• Milestone: 1
Amount (USD): 13,333
Expected Completion Date: 2026-02-15
User Stories:
• “As an infrastructure operator, I want to run predictive maintenance analytics securely, so that I can prevent failures before they occur.”
• “As a researcher, I want access to anonymized blockchain-secured telemetry, so that I can model infrastructure risk trends.”
Deliverables:
• Design finalized for Sentinel Grid x Zcash integration.
• Deployment of private testnet nodes for AI model testing.
• Documentation outlining privacy-preserving data handling.
Acceptance Criteria: Verified operation of testnet with privacy-compliant AI analytics and basic documentation delivered.
⸻
• Milestone: 2
Amount (USD): 13,333
Expected Completion Date: 2026-04-15
User Stories:
• “As a grid operator, I want real-time alerts from AI models, so that I can anticipate energy or communication disruptions.”
• “As a developer, I want a secure API, so that I can integrate Sentinel Grid analytics into my own dashboards.”
Deliverables:
• AI model integrated with Zcash zero-knowledge proof layer.
• API for querying resilience and anomaly detection results.
• Test results and stability metrics.
Acceptance Criteria: Successful end-to-end test demonstrating Zcash-based privacy layer and functional alerting pipeline.
⸻
• Milestone: 3
Amount (USD): 13,334
Expected Completion Date: 2026-06-30
User Stories:
• “As a stakeholder, I want transparent audit trails, so that I can verify AI model integrity and data use.”
• “As an enterprise user, I want to visualize resilience metrics, so that I can optimize resource allocation.”
Deliverables:
• Public testnet demo dashboard with AI results and blockchain proofs.
• Technical documentation and open-source code release.
• Grant report summarizing KPIs and future roadmap.
Acceptance Criteria: Publicly accessible demo, repository published, documentation verified by reviewers.
```
### Supporting Documents
```files.yaml
- File Name 1: Brief description of the file contents
- File Name 2: Brief description of the file contents
```